Finite volume approach of natural convection in a triangular enclosure with localized heating from below

In this study, natural convection heat transfer and buoyancy driven flows have been investigated in a right angled triangular enclosure. The heater located on the bottom wall while the inclined wall is colder and the remaining walls are maintained as adiabatic. Governing equations of natural convection are solved through the finite volume approach, in which buoyancy is modeled via the Boussinesq approximation. Effects of different parameters such as Rayleigh number, aspect ratio, prantdl number and heater location are considered. Results show that heat transfer increases when the heater is moved toward the right corner of the enclosure. It is also revealed that increasing the Rayleigh number, increases the strength of free convection regime and consequently increases the value of heat transfer rate. Moreover, larger aspect ratio enclosure has larger Nusselt number value. In order to have better insight, streamline and isotherms are shown.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

The use of CCTV to police public spaces : a case of big brother or big friend?

This paper considers the role of CCTV (closed circuit television) in the surveillance, policing and control of public space in urban and rural locations, specifically in relation to the use of public space by young people. The use of CCTV technology in public spaces is now an established and largely uncontested feature of everyday life in a number of countries and the assertion that they are essentially there for the protection of law abiding and consuming citizens has broadly gone unchallenged. With little or no debate in the U.K. to critique the claims made by the burgeoning security industry that CCTV protects people in the form of a ‘Big Friend’, the state at both central and local levels has endorsed the installation of CCTV apparatus across the nation. Some areas assert in their promotional material that the centre of the shopping and leisure zone is fully surveilled by cameras in order to reassure visitors that their personal safety is a matter of civic concern, with even small towns and villages expending monies on sophisticated and expensive to maintain camera systems. It is within a context of monitoring, recording and control procedures that young people’s use of public space is constructed as a threat to social order, in need of surveillance and exclusion which forms a major and contemporary feature in shaping thinking about urban and rural working class young people in the U.K. As Loader (1996) notes, young people’s claims on public space rarely gain legitimacy if ‘colliding’ with those of local residents, and Davis (1990) describes the increasing ‘militarization and destruction of public space’, while Jacobs (1965) asserts that full participation in the ‘daily life of urban streets’ is essential to the development of young people and beneficial for all who live in an area. This paper challenges the uncritical acceptance of widespread use of CCTV and identifies its oppressive and malevolent potential in forming a ‘surveillance gaze’ over young people (adapting Foucault’s ‘clinical gaze’c. 1973) which can jeopardise mental health and well being in coping with the ‘metropolis’, after Simmel, (1964).

Removal of epoxy-attached thin-sections from glass slides by plasma-etching

Thin-sectioned samples mounted on glass slides with common petrographic epoxies cannot be easily removed (for subsequent ion-milling) by standard methods such as heating or dissolution in solvents. A method for the removal of such samples using a radio frequency (RF) generated oxygen plasma has been investigated for a number of typical petrographic and ceramic thin sections. Sample integrity and thickness were critical factors that determined the etching rate of adhesive and the survivability of the sample. Several tests were performed on a variety of materials in order to estimate possible heating or oxidation damage from the plasma. Temperatures in the plasma chamber remained below 138°C and weight changes in mineral powders etched for 76 hr were less than ±4%. A crystal of optical grade calcite showed no apparent surface damage after 48 hr of etching. Any damage from the oxygen plasma is apparently confined to the surface of the sample, and is removed during the ion-milling stage of transmission electron microscopy (TEM) sample preparation.

Accurate stratospheric particle-size distributions from a flat-plate collection surface

The first representative chemical, structural, and morphological analysis of the solid particles from a single collection surface has been performed. This collection surface sampled the stratosphere between 17 and 19km in altitude in the summer of 1981, and therefore before the 1982 eruptions of El Chichón. A particle collection surface was washed free of all particles with rinses of Freon and hexane, and the resulting wash was directed through a series of vertically stacked Nucleopore filters. The size cutoff for the solid particle collection process in the stratosphere is found to be considerably less than 1 μm. The total stratospheric number density of solid particles larger than 1μm in diameter at the collection time is calculated to be about 2.7×10−1 particles per cubic meter, of which approximately 95% are smaller than 5μm in diameter. Previous classification schemes are expanded to explicitly recognize low atomic number material. With the single exception of the calcium-aluminum-silicate (CAS) spheres all solid particle types show a logarithmic increase in number concentration with decreasing diameter. The aluminum-rich particles are unique in showing bimodal size distributions. In addition, spheres constitute only a minor fraction of the aluminum-rich material. About 2/3 of the particles examined were found to be shards of rhyolitic glass. This abundant volcanic material could not be correlated with any eruption plume known to have vented directly to the stratosphere. The micrometeorite number density calculated from this data set is 5×10−2 micrometeorites per cubic meter of air, an order of magnitude greater than the best previous estimate. At the collection altitude, the maximum collision frequency of solid particles >5μm in average diameter is calculated to be 6.91×10−16 collisions per second, which indicates negligible contamination of extraterrestrial particles in the stratosphere by solid anthropogenic particles.

Active text perception for mobile robots

Our everyday environment is full of text but this rich source of information remains largely inaccessible to mobile robots. In this paper we describe an active text spotting system that uses a small number of wide angle views to locate putative text in the environment and then foveates and zooms onto that text in order to improve the reliability of text recognition. We present extensive experimental results obtained with a pan/tilt/zoom camera and a ROS-based mobile robot operating in an indoor environment.

Emerging from student to practitioner : a cumulative development tool for students

PURPOSE: This pilot project’s aim was to trial a tool and process for developing students’ ability to engage in self-assessment using reflection on their clinical experiences, including feedback from workplace learning, in order to aid them in linking theory to practice and develop strategies to improve performance. BACKGROUND: In nursing education, students can experience a mismatch in performance compared to theoretical learning, this is referred to as the ‘theory practice gap’ (Scully 2011, Chan Chan & Liu 2011). One specific contributing factor seems to be students’ inability to engage in meaningful reflection and self-correcting behaviours. A self-assessment strategy was implemented within a third year clinical unit to ameliorate this mismatch with encouraging results, as students developed self-direction in addressing learning needs. In this pilot project the above strategy was adapted for implementation between different clinical units, to create a whole of course approach to integrating workplace learning. METHOD: The methodology underpinning this project is a scaffolded, supported reflective practice process. Improved self-assessment skills is achieved by students reflecting on and engaging with feedback, then mapping this to learning outcomes to identify where performance can be improved. Evaluation of this project includes: collation of student feedback identifying successful strategies along with barriers encountered in implementation; feedback from students and teachers via above processes and tools; and comparison of the number of learning contracts issued in clinical nursing units with similar cohorts. RESULTS: Results will be complete by May 2012 and include analysis of the data collected via the above evaluation methods. Other outcomes will include the refined process and tool, plus resources that should improve cost effectiveness without reducing student support. CONCLUSION: Implementing these tools and processes over the entire student’s learning package, will assist them to demonstrate progressive development through the course. Students will have learnt to understand feedback and integrate these skills for life-long learning.

Microanalysis of clays at low temperature

Accurate thin-film energy dispersive spectroscopic (EDS) analyses of clays with low-atomic-number (low Z) elements (e.g. Na, Al, Si), presents a challenge to the microscopist not only because of the spatial resolution required, but also because of their susceptibility to electron beam-induced radiation damange and very low X-ray count rates. Most common clays, such as kaolinite, smectite and illite occur as submicrometer crystallites with varying degrees of structural disorder in at least two directions and may have dimensions as small as one or two unit cells along the basal direction. Thus, even clays with relatively large a-b dimenstions (e.g., 100 x 100 nm) may be <5nm in the c-axis direction. For typical conditions in an analytical electron microscope (AEM), this sample thickness gives rise to very poor count rates (<200cps) and necessitates long counting times (>300s) in order to obtain satisfactory statistical precision. Unfortunately, beam damage rates for the common clays are very rapid (<10s in imaging mode) between 100kV and 200kV. With a focussed probe for elemental analyses, the damage rate is exacerbated by a high current density and may result in loss of low-Z elements during data collection and consequent loss of analytical accuracy.

Numerical methods for strong solutions of stochastic differential equations : an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations

The pioneering work of Runge and Kutta a hundred years ago has ultimately led to suites of sophisticated numerical methods suitable for solving complex systems of deterministic ordinary differential equations. However, in many modelling situations, the appropriate representation is a stochastic differential equation and here numerical methods are much less sophisticated. In this paper a very general class of stochastic Runge-Kutta methods is presented and much more efficient classes of explicit methods than previous extant methods are constructed. In particular, a method of strong order 2 with a deterministic component based on the classical Runge-Kutta method is constructed and some numerical results are presented to demonstrate the efficacy of this approach.

Order conditions of stochastic Runge-Kutta methods by B-series

In this paper, general order conditions and a global convergence proof are given for stochastic Runge Kutta methods applied to stochastic ordinary differential equations ( SODEs) of Stratonovich type. This work generalizes the ideas of B-series as applied to deterministic ordinary differential equations (ODEs) to the stochastic case and allows a completely general formalism for constructing high order stochastic methods, either explicit or implicit. Some numerical results will be given to illustrate this theory.

Mechanical properties of graphene : effects of layer number, temperature and isotope

Herein the mechanical properties of graphene, including Young’s modulus, fracture stress and fracture strain have been investigated by molecular dynamics simulations. The simulation results show that the mechanical properties of graphene are sensitive to the temperature changes but insensitive to the layer numbers in the multilayer graphene. Increasing temperature exerts adverse and significant effects on the mechanical properties of graphene. However, the adverse effect produced by the increasing layer number is marginal. On the other hand, isotope substitutions in graphene play a negligible role in modifying the mechanical properties of graphene.

Procuring OSM : base-line models of off-site manufacture business processes in Australia

A pressing cost issue facing construction is the procurement of off-site pre-manufactured assemblies. In order to encourage Australian adoption of off-site manufacture (OSM), a new approach to underlying processes is required. The advent of object oriented digital models for construction design assumes intelligent use of data. However, the construction production system relies on traditional methods and data sources and is expected to benefit from the application of well-established business process management techniques. The integration of the old and new data sources allows for the development of business process models which, by capturing typical construction processes involving OSM, provides insights into such processes. This integrative approach is the foundation of research into the use of OSM to increase construction productivity in Australia. The purpose of this study is to develop business process models capturing the procurement, resources and information flow of construction projects. For each stage of the construction value chain, a number of sub-processes are identified. Business Process Modelling Notation (BPMN), a mainstream business process modelling standard, is used to create base-line generic construction process models. These models identify OSM decision-making points that could provide cost reductions in procurement workflow and management systems. This paper reports on phase one of an on-going research aiming to develop a proto-type workflow application that can provide semi-automated support to construction processes involving OSM and assist in decision-making in the adoption of OSM thus contributing to a sustainable built environment.

Re-use of domain knowledge to provide confidence for adoption of off-site manufacturing for construction in Australia

Many construction industry decision-makers believe there is a lack of off-site manufacture (OSM) adoption for non-residential construction in Australia. Identification of construction business process was considered imperative in order to assist decision-makers to increase OSM utilisation. The premise that domain knowledge can be re-used to provide an intervention point in the construction process led a team of researchers to construct simple base-line process models for the complete construction process, segmented into six phases. Sixteen domain knowledge industry experts were asked to review the construction phase base-line models to answer the question “Where in the process illustrated by this base-line model phase is an OSM task?”. Through an iterative and generative process a number of off-site manufacture intervention points were identified and integrated into the process models. The re-use of industry expert domain knowledge provided suggestions for new ways to do basic tasks thus facilitating changes to current practice. It is expected that implementation of the new processes will lead to systemic industry change and thus a growth in productivity due to increased adoption of OSM.